Know Systemic Racism Data Lab

Libraries + Data Science + Digital Humanities

The Team, Summer 2023

Anabelle Colmenares

  • Data wrangling
  • Data analysis tools
  • Data visualization
  • Web development

Chloe Williams

  • Data collection
  • Data analysis
  • Data schema design
  • Data archive

Our Partners

Know Systemic Racism Project

  • Systemic Racism Actually Does Exist
  • How Systemic Racism Interconnects
  • How to Help Fight Systemic Racism

What can libraries do?

Provide access to resources.

But our systems of discovery can help perpetuate “othering”.

Categorization has a significant impact on what you can find.

The Role of KSR Data Lab

KSR Data Lab takes the aspiration of KSR — to show that systemic racism exists — as a provocation for thinking critically about data collection/creation, data structures, data access/discovery, and data preservation.

Data Collection/Creation

We are guided by FAIR (Findable, Accessible, Interoperable, Reusable) principles 1 as well as CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles 2.

“The CARE Principles are people– and purpose-oriented, reflecting the crucial role of data in advancing innovation, governance, and self-determination among Indigenous Peoples. The Principles complement the existing data-centric approach represented in the ‘FAIR Guiding Principles for scientific data management and stewardship’”(Carroll et al 2020).

Data Structure

Knowledge Graph

Data Access & Discovery

Multiple points of entry. Rather than seeking discrete data sets, we take advantage of the knowledge graph making connections across collections.

Data Preservation

Stanford Digital Repository Wikidata Archive.org (Internet Archive)

Footnotes

  1. Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. “The FAIR Guiding Principles for scientific data management and stewardship.” Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18

  2. Carroll, Stephanie Russo, et al. “The CARE principles for indigenous data governance.” Data Science Journal 19 (2020): 43-43.